Robots have been deployed across numerous industrial and manufacturing environments to promote reliability and cost savings. Increasingly, they work in the vicinity of human workers; for example, the robot may be required to work collaboratively with humans to perform a task, or the human may enter the robot's workspace by mistake. This can be extremely dangerous, especially if the robot is heavy and moves at a high speed, which is often the case. Conventionally, safety during robot operation is achieved by caging or otherwise safeguarding robots so that humans cannot approach them and, if they do, to ensure that the robots stop in a failsafe manner before a human can get within reach. Recently, safety has been enforced by limiting the inherent capabilities of the robot. A robot may be designed for a particular capability in terms of, for example, its dexterity, force, speed, precision, repeatability, and/or payload capacity; but the flexibility to select optimal parameters may be limited by safety requirements, particularly for robots operating in proximity to humans. Such constraints can make it challenging to achieve safe robot operation relying merely on the inherent robot design.
One alternative to limiting the robot's inherent capabilities is to utilize a safety-rated monitoring system that monitors robotic function and detects any variation therein beyond an allowable limit. For example, the safety-rated monitoring system may continuously monitor the moving speed of a robotic arm; when the detected speed is beyond the allowable limit (which may be context-specific, i.e., lower when humans are present or expected), the monitoring system may command the robot to shut down or work at a drastically reduced speed. Safety-rated monitoring systems are expensive and generally require extra sensors and/or circuitry to be implemented in the robot. They also may be complicated to deploy and use.
Consequently, there is a need for an approach to reliably provide safe robot operation while avoiding unnecessary expense and complexity.